<div class="csl-bib-body">
<div class="csl-entry">de Vries, C., Lombardi, N., & Saorín Gómez, E. (2023). On linearized versions of matrix inequalities. <i>Linear Algebra and Its Applications</i>, <i>674</i>, 21–45. https://doi.org/10.1016/j.laa.2023.05.020</div>
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dc.identifier.issn
0024-3795
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/188102
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dc.description.abstract
In this note, we prove linear versions of the Aleksandrov-Fenchel inequality and the Brunn-Minkowski inequality for positive semidefinite matrices. With this aim, given a positive semidefinite matrix A and a linear subspace L, we consider a family of matrices having the same projection onto L, obtaining a linear version of the Aleksandrov-Fenchel inequality. In the case of the Brunn-Minkowski inequality, the milder assumption of having equal determinant of the projection of A onto L will be enough to obtain a linearized version of this inequality.